- A
Traffic is paused and queued by the Service until replicas are restored
Why wrong: Kubernetes Services don't queue traffic — with 0 backends, requests fail immediately with connection errors.
- B
All Pods are terminated immediately; the Service has no backends and requests fail until replicas are restored
`scale --replicas=0` terminates all Pods. The Service loses all endpoints and incoming traffic fails. Running `kubectl scale --replicas=3` restores the Pods.
- C
GKE detects the replica count is 0 and automatically restores it to maintain high availability
Why wrong: GKE respects the desired replica count set by the user — it doesn't override explicit user commands to scale to 0.
- D
The Deployment is paused but Pods continue running until the next rollout
Why wrong: `scale --replicas=0` doesn't pause a Deployment — it immediately terminates all Pods. `kubectl rollout pause` pauses rollout but leaves existing Pods running.
Quick Answer
The answer is that all traffic immediately fails with connection errors or HTTP 503 responses because scaling a deployment to zero replicas terminates every Pod at once. This happens because a Kubernetes Service relies on healthy endpoints—the Pods’ IP addresses—to route traffic; when you run `kubectl scale deployment api-service --replicas=0`, the Deployment controller deletes all Pods, the Service’s endpoint list empties, and any incoming request has no backend to receive it. On the Google Associate Cloud Engineer exam, this scenario tests your understanding that scaling to zero is not a graceful pause—it is an immediate shutdown, and the Service does not queue or buffer traffic. A common trap is assuming the Service will hold requests or that a load balancer will retry automatically; in reality, clients see instant failures until you scale back up. Memory tip: zero replicas means zero endpoints, so traffic hits a dead end.
Google ACE Deploying and implementing a cloud solution Practice Question
This ACE practice question tests your understanding of deploying and implementing a cloud solution. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A GKE Deployment is running 3 replicas and receiving steady traffic. A junior engineer runs `kubectl scale deployment api-service --replicas=0` to 'stop it temporarily'. What happens to traffic during and after this command?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
All Pods are terminated immediately; the Service has no backends and requests fail until replicas are restored
When you scale a Deployment to 0 replicas, `kubectl` immediately terminates all Pods. The associated Kubernetes Service continues to exist but has no healthy endpoints, so any traffic directed to the Service’s ClusterIP or external load balancer will be dropped or result in a connection refusal (TCP RST) or HTTP 503. Traffic is not queued or buffered; it simply fails until new Pods are created by scaling the Deployment back up.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Traffic is paused and queued by the Service until replicas are restored
Why it's wrong here
Kubernetes Services don't queue traffic — with 0 backends, requests fail immediately with connection errors.
- ✓
All Pods are terminated immediately; the Service has no backends and requests fail until replicas are restored
Why this is correct
`scale --replicas=0` terminates all Pods. The Service loses all endpoints and incoming traffic fails. Running `kubectl scale --replicas=3` restores the Pods.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
GKE detects the replica count is 0 and automatically restores it to maintain high availability
Why it's wrong here
GKE respects the desired replica count set by the user — it doesn't override explicit user commands to scale to 0.
- ✗
The Deployment is paused but Pods continue running until the next rollout
Why it's wrong here
`scale --replicas=0` doesn't pause a Deployment — it immediately terminates all Pods. `kubectl rollout pause` pauses rollout but leaves existing Pods running.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that Kubernetes Services can queue or buffer traffic during scaling events, when in reality they are stateless and rely on real-time endpoint availability.
Trap categories for this question
Command / output trap
GKE respects the desired replica count set by the user — it doesn't override explicit user commands to scale to 0.
Detailed technical explanation
How to think about this question
Under the hood, `kubectl scale` updates the Deployment’s `spec.replicas` field, which causes the ReplicaSet controller to reconcile by deleting all Pods. The EndpointSlice controller watches Pod readiness and removes the Pod IPs from the Service’s endpoints; once the last Pod is gone, the Service’s `spec.clusterIP` has no backing endpoints, and kube-proxy’s iptables or IPVS rules will forward traffic to a null target (or reject it depending on the proxy mode). In GKE, if the Service is of type LoadBalancer, the external load balancer health checks will fail and the load balancer will stop forwarding traffic, resulting in client connection errors.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this ACE question test?
Deploying and implementing a cloud solution — This question tests Deploying and implementing a cloud solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: All Pods are terminated immediately; the Service has no backends and requests fail until replicas are restored — When you scale a Deployment to 0 replicas, `kubectl` immediately terminates all Pods. The associated Kubernetes Service continues to exist but has no healthy endpoints, so any traffic directed to the Service’s ClusterIP or external load balancer will be dropped or result in a connection refusal (TCP RST) or HTTP 503. Traffic is not queued or buffered; it simply fails until new Pods are created by scaling the Deployment back up.
What should I do if I get this ACE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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